More and more, people are interacting with and through online services, including but not limited to social networking sites, search engines, online shopping sites, libraries, entertainment/gaming sites, music and video streaming sites, and the like. All of these online services work at a basic level of functionality with each new (or unidentified) user, yet nearly all of these online services work “better” when a user provides information about himself/herself to the service. With specific information about the user, these online services are able to “personalize” their services—i.e., provide services specifically tailored and targeted to the user. Frequently these online services also “share” information regarding their users in order to expand their knowledge of each of “their” users.
As part of personalizing the service to a user, these online services will often make recommendations to the user of a product, a service, available content, and the like. For example, a social networking site may recommend people or groups with whom you may wish to associate. A search engine may recommend content, entities, and/or alternative search queries. Similarly, a video streaming service may recommend one or more videos it believes that may interest the user. Sometimes a user will understand the basis of a recommendation from a search service. However, quite often the user cannot understand the basis of a recommendation, i.e., the relationship between the user and a personalized or recommended item. When this occurs, the user is understandably suspicious of the item and why it was presented, and directly impacts the user engagement of a recommendation.